Jump risk premia in the presence of clustered jumps¶
Bibliographic record. Follow the original-source link for the publication.
| Field | Value |
|---|---|
| Primary domain | Option Returns |
| Other domains | Volatility, Hedging Exposure Risk |
| Methods | — |
| Facets | — |
| Authors | Francis Liu, Natalie Packham, Artur Sepp |
| Published | 2025-10-24 |
| Source | arXiv Quantitative Finance History |
| Identifiers | arxiv:2510.21297 |
| URL | Open original source |
Editorial synthesis¶
Why it matters¶
This preprint introduces clustered jumps with sign-specific jump risk premia in option pricing, relevant to dynamic skew behavior and sentiment-driven pricing adaptation, though only abstract-level evidence is provided. (abstract:S1, abstract:S2, abstract:S3, abstract:S4, abstract:S5, abstract:S6)
Main author claims¶
- The authors claim a bivariate Hawkes process for clustered jumps captures self- and cross-excitation of positive and negative jumps, producing time-varying skewness and skews of either sign. (
abstract:S1,abstract:S2) - They further claim inferred positive and negative jump premia, identified from options data, show predictive power for BTC futures carry cost and delta-hedged option-strategy performance. (
abstract:S4,abstract:S5,abstract:S6)
Data, method, or discussion scope¶
The scope includes abstract-level model mechanics and BTC empirical claims, with no jump-threshold selection, estimation uncertainty, or explicit OOS test diagnostics provided. (abstract:S1, abstract:S2, abstract:S3, abstract:S4, abstract:S6)
Main limitations¶
Empirical evidence is centered on BTC, limiting direct generalization, and claims of skew dynamics and predictive power are not tied to explicit significance standards or OOS loss definitions. (abstract:S3, abstract:S6, abstract:S4)
Relationships¶
- None recorded.